code: def test_score(nrows, ncols, n_neighbors, n_clusters, datatype):
      X, y = make_blobs(
          n_samples=nrows,
          centers=n_clusters,
          n_features=ncols,
          random_state=0,
          cluster_std=0.01,
      )
  
      X = X.astype(np.float32)
      X_train, X_test, y_train, y_test = _build_train_test_data(
          X, y, datatype
      )
  
      knn_cu = cuKNN(n_neighbors=n_neighbors)
      knn_cu.fit(X_train, y_train)
  
      assert knn_cu.score(X_test, y_test) >= (1.0 - 0.004)
  
file_path: cuml/python/cuml/tests/test_kneighbors_classifier.py
imports: from cuml.testing.utils import array_equal
  from cuml.internals.safe_imports import cpu_only_import
  from sklearn.datasets import make_blobs
  from sklearn.neighbors import KNeighborsClassifier
  from cuml.neighbors import KNeighborsClassifier
  import cuml
  import pytest
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 3 for calling a global function with example usage: test_score(nrows, ncols, n_neighbors, n_clusters, datatype) without return types